Signal+Processing
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KAIST to Develop a Korean-style ChatGPT Platform Specifically Geared Toward Medical Diagnosis and Drug Discovery
On May 23rd, KAIST (President Kwang-Hyung Lee) announced that its Digital Bio-Health AI Research Center (Director: Professor JongChul Ye of KAIST Kim Jaechul Graduate School of AI) has been selected for the Ministry of Science and ICT's 'AI Top-Tier Young Researcher Support Program (AI Star Fellowship Project).' With a total investment of ₩11.5 billion from May 2025 to December 2030, the center will embark on the full-scale development of AI technology and a platform capable of independently inferring and determining the kinds of diseases, and discovering new drugs.
< Photo. On May 20th, a kick-off meeting for the AI Star Fellowship Project was held at KAIST Kim Jaechul Graduate School of AI’s Yangjae Research Center with the KAIST research team and participating organizations of Samsung Medical Center, NAVER Cloud, and HITS. [From left to right in the front row] Professor Jaegul Joo (KAIST), Professor Yoonjae Choi (KAIST), Professor Woo Youn Kim (KAIST/HITS), Professor JongChul Ye (KAIST), Professor Sungsoo Ahn (KAIST), Dr. Haanju Yoo (NAVER Cloud), Yoonho Lee (KAIST), HyeYoon Moon (Samsung Medical Center), Dr. Su Min Kim (Samsung Medical Center) >
This project aims to foster an innovative AI research ecosystem centered on young researchers and develop an inferential AI agent that can utilize and automatically expand specialized knowledge systems in the bio and medical fields.
Professor JongChul Ye of the Kim Jaechul Graduate School of AI will serve as the lead researcher, with young researchers from KAIST including Professors Yoonjae Choi, Kimin Lee, Sungsoo Ahn, and Chanyoung Park, along with mid-career researchers like Professors Jaegul Joo and Woo Youn Kim, jointly undertaking the project. They will collaborate with various laboratories within KAIST to conduct comprehensive research covering the entire cycle from the theoretical foundations of AI inference to its practical application.
Specifically, the main goals include: - Building high-performance inference models that integrate diverse medical knowledge systems to enhance the precision and reliability of diagnosis and treatment. - Developing a convergence inference platform that efficiently combines symbol-based inference with neural network models. - Securing AI technology for new drug development and biomarker discovery based on 'cell ontology.'
Furthermore, through close collaboration with industry and medical institutions such as Samsung Medical Center, NAVER Cloud, and HITS Co., Ltd., the project aims to achieve: - Clinical diagnostic AI utilizing medical knowledge systems. - AI-based molecular target exploration for new drug development. - Commercialization of an extendible AI inference platform.
Professor JongChul Ye, Director of KAIST's Digital Bio-Health AI Research Center, stated, "At a time when competition in AI inference model development is intensifying, it is a great honor for KAIST to lead the development of AI technology specialized in the bio and medical fields with world-class young researchers." He added, "We will do our best to ensure that the participating young researchers reach a world-leading level in terms of research achievements after the completion of this seven-year project starting in 2025."
The AI Star Fellowship is a newly established program where post-doctoral researchers and faculty members within seven years of appointment participate as project leaders (PLs) to independently lead research. Multiple laboratories within a university and demand-side companies form a consortium to operate the program.
Through this initiative, KAIST plans to nurture bio-medical convergence AI talent and simultaneously promote the commercialization of core technologies in collaboration with Samsung Medical Center, NAVER Cloud, and HITS.
2025.05.26 View 928 -
Professor Jong Chul Ye Appointed as Distinguished Lecturer of IEEE EMBS
Professor Jong Chul Ye from the Department of Bio and Brain Engineering was appointed as a distinguished lecturer by the International Association of Electrical and Electronic Engineers (IEEE) Engineering in Medicine and Biology Society (EMBS). Professor Ye was invited to deliver a lecture on his leading research on artificial intelligence (AI) technology in medical video restoration. He will serve a term of two years beginning in 2020.
IEEE EMBS's distinguished lecturer program is designed to educate researchers around the world on the latest trends and technology in biomedical engineering. Sponsored by IEEE, its members can attend lectures on the distinguished professor's research subject.
Professor Ye said, "We are at a time where the importance of AI in medical imaging is increasing.” He added, “I am proud to be appointed as a distinguished lecturer of the IEEE EMBS in recognition of my contributions to this field.”
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2020.02.27 View 11504 -
Prof. Jong Chul Ye Appointed as the Editor of IEEE TIP
Professor Jong Chul Ye
KAIST Bio & brain engineering department’s Professor Jong Chul Ye has been appointed as the editor of the "IEEE image processing transactions (IEEE TIP, IEEE Transaction on Image Processing)’, a prominent journal in the sector of imaging and medical image processing.
Professor Ye will act as the editor in the field of medical imaging from February 2013 to January 2016, during which he will participate in examining thesis, establishing the direction of the journal and more.
Professor Jong Chul Ye was recognized for his notable work in the field of medical imaging research using compressed sensing for the development of a high resolution medical image reconstruction techniques. This technique has pioneered a new area that is applicable in magnetic resonance imaging (MRI), computed tomography (CT), positron emission Camcorder (PET) and brain imaging.
On the other hand, “IEEE TIP” was first published in 1992 and is currently the world’s leading authority in the field of image processing, medical imaging, image acquisition, compression and output.
2013.02.21 View 11049 -
KAIST Wins First Prize at Recon Challenge of Int"l Magnetic Resonance Society
Professor Jong-chul Ye of the Department of Bio and Brain Engineering and Hong Jeong, a doctorate student, won the first prize at the Recon Challenge held as part of a workshop sponsored by the International Society for Magnetic Resonance in Medicine (ISMRM) held in Sedona, the United States.
The workshop took place under the theme of “data sampling and image reconstruction” on Jan. 25-28 in Sedona, Arizona, the United States. The KAIST team beat out major magnetic resonance imaging groups from the U.S. and Europe.
The Recon Challenge is a biennial competition highlighting different reconstruction strategies and metrics to compare them. ISMRM is an international, nonprofit, scientific association which promotes communication, research, development, and applications in the field of magnetic resonance in medicine and biology and other related topics.
At the competition, the KAIST team presented a new dynamic MRI algorithm called k-t FOCUSS that is optimal from a compressed sensing perspective. The main contribution of the method is extension of k-t FOCUSS to a more general framework with prediction and residual encoding. The prediction provides an initial estimate while the residual encoding takes care of the remaining residual signals.
2009.02.06 View 15248 -
Professor Ikho Song Wins Academic Award of Haedong Information & Communication
Professor Ikho Song Wins Academic Award of Haedong Information & Communication
Professor Ikho Song (Division of Electrical Engineering) won an academic award of Haedong Information & Communication at a regular meeting of Korean Institute of Communication Sciences 2006. The award was given to Professor Song in recognition of his presenting excellent papers at many renowned domestic and global academic journals and his substantial contribution to the development of the information & communication field.
Meanwhile, Hyungmoon Kwon, a doctorate student under Professor Song’s supervisory, also won an award of excellent paper at the meeting.
2006.11.27 View 13872